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All Journal Jurnal Keteknikan Pertanian Tropis dan Biosistem Jurnal Medik Veteriner
Sule, Shakiru Okanlawon
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Control & Systems Engineering Electrical & Electronics Engineering Energy Mechanical Engineering Veterinary

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Effect of Gum Arabic (Acacia senegal) on Growth Performance, Carcass Quality and Health of Clarias gariepinus Juveniles Falaye, Augustine Eyiwunmi; Abah, Abel; Sule, Shakiru Okanlawon
Jurnal Medik Veteriner Vol. 7 No. 1 (2024): April
Publisher : Universitas Airlangga

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20473/jmv.vol7.iss1.2024.163-176

Abstract

The effect of Gum Arabic (GA) on growth, carcass quality, blood parameters, gut morphometry, and organ histology of African catfish Clarias gariepinus was studied. Five isonitrogenous diets with inclusion levels of GA at 0 g/100 g (GA0; control), 5 g/100 g (GA5), 10 g/100 g (GA10), 15 g/100 g (GA15), and 20 g/100 g (GA20) were formulated in a 40% crude protein diet. Juveniles of C. gariepinus with average weight (7.35±0.48 g/fish) were stocked at 13 fish/25 L of water for 12 weeks in a completely randomized design and fed at 3% body weight daily. Growth indices showed GA10 improved the mean weight gain (69.88±8.89 g) and specific growth rate (2.76±0.14 %/day) while at (GA15); (GA20) growth was depressed. Carcass quality revealed dietary levels were superior to control with GA10 significantly different (p < 0.05) amongst treatments in protein and fat content. Hematological profile showed variations; erythrocyte indices compared to control, while plasma chemistry of aspartate aminotransferase, alkaline phosphatase, and alanine aminotransferase showed no difference (p > 0.05). Gut morphometrics varied with no particular pattern. At inclusion above GA5 the gill, liver, and kidney were affected histologically with no changes in the intestines of all treatments. Diet supplemented with gum arabic at 10 g/100 g improved indices of performance of C. gariepinus juveniles in this study.
Effects of Operational Factors on The Productivity, Efficiency, And Power Consumption of a Fish Meal Pelleting Machine Kosemani, Babajide; Sule, Shakiru Okanlawon; Adewumi, Idowu Olugbenga; Afolabi, Bukola Olanrewaju; Mufutau, Monsuru Olayinka
Jurnal Keteknikan Pertanian Tropis dan Biosistem Vol. 14 No. 2 (2026): August 2026
Publisher : Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/

Abstract

Pelletizing remains one of the most economical and technologically advanced techniques for producing fish feed. The quality characteristics of the resulting pellets are influenced by several operational variables, which, when improperly controlled, can lead to suboptimal feed quality. This research work optimizes some operational parameters including die size, shaft speed and feeding rate of an indigenous fish meal pelletizing machine for productivity, efficiency, power consumption and specific energy consumption. Mixed fish feed materials were pelletized at 29, 31 and 31m/s die speed, loaded onto the pelleting machine at different feeding rates (15, 20, and 25kg/hr) and die hole (3, 4, 5). The RSM was employed to improve the machine performance by analysing the impact of multiple operational variables on the response including productivity, efficiency, power consumption and specific energy consumption. The interaction of the operational parameters and response factors were established through Quadratic models. The impact of the operational parameters on productivity, efficiency, power consumption and specific energy consumption were significant (p ?0.01). The optimal condition of the process for die speed, die hole and feeding rate were 31m/s, 5mm and 20kg/hr, respectively, resulting in machine productivity, efficiency, power consumption and specific energy consumption of 82.02kg/hr, 86.09%, 2.55kW, and 0.029 kWh/kg, respectively. This indicates that the fish meal pelletising machine ran efficiently under optimal conditions, therefore validating the generated models.
Co-Authors Abah, Abel Adewumi, Idowu Olugbenga Afolabi, Bukola Olanrewaju Falaye, Augustine Eyiwunmi Kosemani, Babajide Mufutau, Monsuru Olayinka